基于改进差分进化算法的多目标第Ⅰ类装配线平衡问题研究

发布时间：2018-03-05 18:43

  本文选题：第Ⅰ类装配线平衡问题　切入点：多目标优化　出处：《科技通报》2017年11期 　论文类型：期刊论文

【摘要】：为求解多目标第Ⅰ类装配线平衡问题(MOABLP-Ⅰ),提出了一种改进的差分进化算法(IDEA)。该算法优化目标包括最优工位数,线生产效率和工位载荷波动。采用基于优先权的编码方法使得个体解码后总满足装配线约束关系,设计了自适应双变异策略和新型交叉操作算子使算法适应离散优化问题,引入"精英保留"机制增强算法逃离局部最优的能力。通过测试问题集的验证,并比较了基本差分进化算法和离散型差分进化算法,结果表明IDEA在求解大规模MOABLP-Ⅰ上质量最优。
[Abstract]:In order to solve the multiobjective class I assembly line balance problem, an improved differential evolutionary algorithm (DEA) is proposed. The optimization goal of the algorithm includes the optimal number of stations. The efficiency of line production and load fluctuation of work station are fluctuated. The coding method based on priority is used to make the individual satisfy the assembly line constraint relationship after decoding. Adaptive double mutation strategy and new crossover operator are designed to adapt the algorithm to discrete optimization problem. The "elite reservation" mechanism is introduced to enhance the ability of the algorithm to escape from the local optimum. The basic differential evolution algorithm and the discrete differential evolution algorithm are compared by the test problem set. The results show that IDEA is the best in solving large-scale MOABLP- 鈪，

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